The Executive’s Playbook for Decision Model Innovation (Part 9)

Where Customer Centricity meets Decision Intelligence

Step 5: Build the Delivery System

Core concept: With a solid design and business model for our decision-support innovation, Step 5 addresses execution: how do we actually deliver this new value to customers reliably and at scale? This involves aligning people, processes, and technology. We must ask: Which processes and roles must change so that employees deliver on the new proposition? What tech architecture is needed to embed the decision support into everyday workflows (ours or the customer’s)? And how do we sequence pilots, rollout, and scale-up to implement the innovation successfully?​file-7jjafxghwtnw5fgbhquqta. In short, we’re ensuring the organisation can do DMI, not just plan it.

Organisational and process changes: A common mistake in innovation is bolting a new service onto old processes. Decision Model Innovation often requires a shift in how the company operates because you’re now in the business of providing ongoing advice/insights, not just selling a product and walking away. So we review our internal processes and roles through the lens of the new proposition. For example, if we historically manufactured widgets and shipped them, but now we’re adding a digital decision-support app that utilises those widgets, we might need a new Customer Success function to ensure customers use and derive value from the app. Employees in sales and support need training to pitch and assist with this new service, not just the physical product. In some cases, entirely new roles emerge, such as data scientists to refine recommendation algorithms or “decision coaches” who can provide complex guidance to customers.

Consider a B2B scenario: a company selling industrial pumps decides to offer a real-time dashboard to help clients make informed decisions about maintenance and energy optimisation. Delivering this means the company’s support engineers now play a proactive advisory role, not just waiting for breakdown calls. They may need a new process, such as a periodic review meeting with the client to go over the dashboard insights. The company may establish a Decision Support Team that monitors client data and provides recommendations. This is a new process, distinct from the reactive support model that preceded it. It might also tie into how salespeople operate: instead of selling a pump and moving on, they might now be expected to stay engaged and ensure the client adopts the decision dashboard (perhaps they receive KPIs related to the service's usage). We should formalise these changes: update job descriptions, create playbooks for how staff should incorporate the decision-support element. Communication channels may need updating – for example, front-line employees require easy access to customer data and analytics insights to have informed conversations.

Internally, we may need to break down some silos. Delivering a tech-enabled service may require close cooperation among the product team (building the tool), the IT/data team, and the customer-facing teams. Some organisations form a cross-functional task force or squad for the new offering, combining marketing, engineering, operations, and support. This echoes agile or “two-pizza team” concepts, such as those found at Amazon, where small teams own a product from end to end. If our decision-support is initially a pilot, we might run it with a dedicated team that acts almost like a startup within, to iron out kinks before integrating broadly.